Using Fly Ball Distance to Find Sleeper Prospects

Dodgers’ prospect Carlos Rincon could be a breakout prospect thanks in part to his average fly ball distance. (via Joel Dinda)

One sunny, beautiful afternoon in April, while sitting at his computer a mere 25 kilometers north of Lake Ontario, this writer submitted a bid for Franmil Reyes in the Ottoneu FanGraphs Staff League. The bid went unopposed. Glossing over the abysmal performance of said author in said league, this bid, which remains as yet mediocre, was based on one stat: Franmil’s adjusted fly ball distance in Double-A at a young enough age to be meaningful.

I suppose, technically, it is actually one statistic and one biographical detail, namely the player’s age. To be even more specific, it’s a maximum age of 22 years. Why 22? We’ll look at the data in a bit and demonstrate why. It’s not a Deep LearningTM method. Rather, it’s a human look at the data, identifying the cluster that gives us a meaningful, predictive subset. The small group of athletes who graduate to the majors are all outliers who should exhibit outlier ability. In this case, the ability to combine launch angle and power to drive the ball consistently farther than their peers.

Adjusted Fly Ball Distance (FB Dist+) is a relative measure of fly ball distance hit, based on all fly balls hit for an out or a home run, with 100 being the average. An average FB Dist+ of 100 translates to roughly 275 feet. However, the important metric is the number relative to the average, rather than the raw number. The methodology is covered in greater detail in my first piece on the subject. You may want to skip my second piece, where I tried to convince you that Dylan Cozens is the next big thing. I’ve since tweaked the data in this piece to adjust for stadium bias in fly ball distance, which has improved the reliability of the metric. We’ll look at all levels of the minor leagues where we have reliable data, starting in Low-A and work our way up to Triple-A.

Before we begin our exploration, let’s set a baseline for what the FB Dist+ metric translates to in terms of ability. We’ll do this by measuring how many batters in a given season and level perform at elite levels, thus demonstrating what constitutes outlier ability.

FB Dist+ Cumulative Distribution at Double A

We’re looking at a cumulative distribution of FB Distance+, filtered to include non-pitcher seasons with at least 30 balls in play. As we approach 107 and above, we’re looking at the top five percent of batter seasons. The distributions for other levels of the minors are consistent with what we see in Double-A, suggesting that elite ability to drive the ball is somewhere around the 106 to 107 FB Dist+ mark. With this number in mind, let’s begin our exploration, starting at the Low-A level:

Low-A FB Dist+ & Age

We don’t see a whole lot of encouraging data at this level. Joey Gallo is a clear outlier, but so is Saquan Johnson. Greg Bird is clustered close to Franchy Cordero, but they are surrounded by Stone Garrett, BJ Boyd and Brandon Wagner. Although we can’t draw any strong conclusions from these data, direct your attention to the right side of the chart, specifically the cluster around the age-18 mark, consisting of Victor Robles, Jorge Alfaro, Israel Pineda and Anderson Franco. These players all exhibited near-elite levels of fly ball distance at a very young age. Pineda in particular is very interesting and I think should pop up on prospect lists in the near future. Let’s move on to Single-A batters, and see if we get a more defined cluster.

Single-A FB Dist+ & Age

Now there’s an interesting list. Just below our somewhat arbitrary cut-off line, we have the Juniors Ronald and Vladimir. More importantly, we have a near flawless cluster of young talent (those in the top-right quadrant), simply by spinning around our two metrics. This rudimentary view would suggest that we should be giving more prospect cred to Bobby Bradley, who profiles similarly to Matt Olson. Any good process should pop out a couple of interesting outliers; here we see Khalil Lee and Will Banfield. Lee is very intriguing as a smaller player (he is 5-foot-10 and 170 pounds) projected to have 55 game power, whose clustering around Xander Bogaerts, Corey Seager and Gary Sanchez would indicate that he has a very good chance at tapping into his potential. Will Banfield is also intriguing, though his FB Dist+ metric comes with a relatively small sample size of 33 balls in play. However, his relatively young age while producing elite fly ball distances suggest he has a lot of upside. Juan Soto’s 2018 season is split out from his 2017 during which he wasn’t healthy. Clearly, his elite average fly ball distance was a sign of good things to come.

High-A FB Dist+ & Age

The cluster generated for High-A is arguably not as compelling as the Single-A list due to the presence of Alen Hanson, K.J. Woods and Julio Morban. Carlos Rincon, who posted a 220 wRC+ in High A looks like the type of prospect who will “come out of nowhere” to rocket up prospect lists. Eric Longenhagen, FanGraphs’ lead prospect analyst, described him as a 40 or 40+FV with huge raw power in an organization that’s good at unlocking it. Gareth Morgan is clearly selling out for his power numbers, as evidenced by his exorbitant 53.9 percent strikeout rate and 68 wRC+ despite a .228 ISO. There is a very intriguing cluster of batters aged 19.5 to 20 with a FB Dist+ between 107 and 108: Carlos Correa, Jo Adell, Corey Seager, Cody Bellinger, Kyle Tucker and Austin Riley.

A couple of names to keep track of: Jazz Chisholm, who is directly on the cutoff line, as well as Jose Gutierrez, who is clustered close to Gleyber Torres, albeit with a lot more swing-and-miss. We are dealing with a small sample size with Gutierrez and while he may not scream top prospect, there is enough there that he might become relevant soon.

The chart above stresses the importance of youth in projecting a prospect. If you look to the right of the arbitrary age line, we see far fewer misses among prospects with at least a 104 FB Dist+. Above that threshold, we have a few hits, such as Kris Bryant, but a lot of prospects who just never went anywhere. Let’s move on up to Double A.

Double-A FB Dist+ & Age

A Hardball Times Update
Goodbye for now.

We’ve drawn two lines here on the fly ball distance axis, one at 106 and one at 112. The 112 line is significant in that batters who had an average age of 23 or under and posted a 112 FB Dist+ or greater have been very successful in the majors. If you aren’t all in on Yordan Alvarez yet, get excited now. He generates Joey Gallo type power, with significantly less swing and miss; Alvarez is 23 percent better than his peers, while Gallo was about 100 percent worse than his. He may be more of a fantasy baseball asset than a real-life WAR generator due to his defensive shortcomings, but when he arrives he should hit for average and plenty of power.

This cluster of talent bodes well for the uniquely named Hudson Potts. I would suggest that despite his abysmal 40 wRC+ and .077 ISO at Double-A, Potts is a very, very high ceiling guy. He may need a couple of years to “figure it out,” but his combination of youth and power portends a bright future. Further, his 37.1 K% at Double-A wasn’t a byproduct of huge swing and miss in his game, so it should regress back to his levels in High-A and Single-A. The only caveat with Potts is the relatively small sample size (47 balls in play) we have for him in Double-A. On the surface, a 112 FB Dist+ does not appear to be all that much higher than 111. However, as noted in the cumulative distribution chart, it is exponentially more difficult to increase your fly ball distance the higher up the curve you go. The only name on the chart that I expect may end up as a bust is Dylan Cozens, who has been atrocious so far. However, it is too early in his career to write him off.

It’s always encouraging when we get a cluster of young superstars who just make sense together. The Juniors Acuña and Guerrero sandwich Bryce Harper. In case you’re wondering, Mike Trout posted only a 101 FB Dist+ at this point in his career, though his whiff rate was 58 percent better than his peers. This methodology is not intended to create a over-arching prospect list. Rather, it is an interesting way to capture a select group of players who will likely have enough time on their side to tap into their natural raw power. Mike Trout isn’t the best player in baseball because he hits as hard as Aaron Judge; he’s the best because he makes consistently good contact (low standard deviation of launch angle) with enough power to make it play up. If you needed another reason to be excited about Vladimir Guerrero Jr., I’ll point out that he’s basically Ronald Acuña with less swing and miss.

Franmil Reyes is right on that arbitrary age-22 line I mentioned at the top of the article, clustered around mediocre prospects like Cesar Puello, Willy Garcia and Nellie Rodriguez. He’s also near Austin Hays, Eloy Jimenez and Miguel Sano. Reyes’ 6-foot-5, 275-pound frame, mixed with his demonstrated ability to tap into that powerful frame in-game, is enough to suggest he may have been a tweak or two away from being a legit major league slugger.

An interesting name to keep an eye on is Deivi Grullon, who is not currently among the top-ranked Miami prospects but is directly next to the grey dot representing Greg Bird. There are a lot more false positives in this area of the chart, but it does bode well for Grullon’s prospects, especially if he can stick at catcher.

A little-known prospect, Andy Pineda, looks poised to climb prospect lists. Keep an eye on him, especially for deep keeper-style leagues like Ottoneu. The true test for methodologies like these are their ability to pick out guys missed by more traditional methods. This author hopes that Pineda and Grullon (both currently unranked) prove out the methodology by becoming relevant in the near future.

Let’s move on to Triple-A.

Triple -A FB Dist+ & Age

We see a similar pattern in Triple-A, where the number of successful prospects in the upper-right quadrant is extremely high, with a much lower success rate for prospects anywhere else. One name that pops out is Lane Thomas, who posted a very impressive fly ball distance despite hitting just six home runs in Triple-A and having a relatively pedestrian 110 wRC+. Thomas, based on the above chart, is poised to be the latest in a long line of St. Louis hitters who explode onto the scene after flying under the radar for most of their career. He also had significantly less swing-and-miss than the players he is closest to on the chart (Joc Pederson, Kyle Schwarber and Matt Chapman), all of whom have had success at the big league level. Speaking of Chapman, I’d like to say that his FB distance was portentous, but he is clustered around Carlos Peguero, Ryan Lavarnway and J.D. Davis. I’m not sure what to make of Davis yet. It is difficult to tell whether he’s a Quad-A guy, or if there is room for growth.


There are many complex, sophisticated models used to evaluate prospects today that integrate a multitude of factors into their algorithms. Today, we looked at a very simple model, which simply evaluated prospects based on their fly ball distance and age, and were able to produce a very consistently compelling subset of prospects, all the way from Low-A to Triple-A. Along the way, we discovered that we should perhaps be paying more attention to Israel Pineda, Hudson Potts, Andy Pineda, Deivi Grullon, Lane Thomas and Jose Gutierrez.

FanGraphs has created a dedicated page for prospect coverage. Be sure to check it out.

Eli Ben-Porat is a Senior Manager of Reporting & Analytics for Rogers Communications. The views and opinions expressed herein are his own. He builds data visualizations in Tableau, and builds baseball data in Rust. Follow him on Twitter @EliBenPorat, however you may be subjected to (polite) Canadian politics.
Newest Most Voted
Inline Feedbacks
View all comments
5 years ago

Isn’t fly ball distance a measure of a batter’s ability to consistently make solid contact and not power to hit the ball? I would think that if you want to measure power to hit the ball, you’d measure only the distance of HRs or something that requires solid contact. If a player takes a strategy to protect the plate with 2 strikes, it will negatively impact his average fly ball distance, obviously without changing his power to hit the ball.

5 years ago

This is excellent — one of the best articles I have read all year.

One question: are the colors of the dots supposed to signify anything? Is there a way to tell whether the player is currently at that level, or if it is historical data (for names that are not obvious)?


5 years ago

Why is Cesar Puello mediocre? I’ve seen his AAA #s and wondered why he doesn’t get a chance… Sub-par defender and not enough pop?

5 years ago
Reply to  Strong_Belwas

Love the name, that is all.

Billy Corman
5 years ago

Is FB Dist+ cataloged as a stat anywhere other than your personal computer. I love simple underlying metrics like this. Also, while the cutoff is 22-yr olds, are there any indicators for the late bloomers, i.e. a 26-yr old tapping into power like Josh Donaldson?

5 years ago

First of all, it was nice meeting you at the FG meetup in Denver. If you don’t remember me, I was the short annoying dude.

Secondly, nicely done. I definitely like seeing validation for picking up Lane Thomas in my dynasty league. Gotta dig deep with 18 teams and 50 prospect slots per.

D.K. Willardsonmember
5 years ago

Interesting article. A very important factor that could be added to this analysis is where the distance is coming from. In other words, players who are consistently getting added distance from backspin perform well below average. Regular players who are in the lowest quartile for backspin distance (i.e. “square hitters”) for 2015-2017 include Mike Trout, Kris Bryant, Miguel Cabrerra, Joey Votto, and Christian Yelich.

The best player in the high backspin group over the same period was Mookie Betts with an average wRC+ of 123.

Who had one of the largest reductions in backspin distance in 2018? —Mookie Betts. Research was posted on Fangraphs in August on backspin if you’re interested.